Apart from the aforementioned evaluation methods, some new methods have also been proposed over these years. For example, Zhang et al. [1]} proposed \(Ranker\)  to learn the ranking orders of NR-IQA methods (i.e., NIQE) on the results of some perceptual SR models. Zhang et al.[2]} introduced a new dataset of human perceptual similarity judgments. Meanwhile, a perceptual evaluation metric, Learned Perceptual Image Patch Similarity (LPIPS), is constructed by learning the perceptual judgement in this dataset. In summary, how to measure the perceptual quality of SR images more accurately and efficiently is an important issue that needs to be explored.
